A Fast Implementation of Factor Analysis for Speaker Verification

The problem of session variability in text-independent speaker verification has been
tackled actively for a few years. The factor analysis approach has been successfully
applied for solving the session variablity problem. However, it suffers from a large
amount of computational overhead. In this paper, a fast implementation of factor analysis
approach with GMM Gaussian pre-selection is proposed. In our method, the EM statistics are
calculated only using the Gaussians selected by cluster UBM to improve the speed of
estimating factor analysis model. Experimental results on the NIST SRE 2006 evaluation
show that the presented approach can provide as much as a 7 to 8x speedup over the
baseline factor analysis system with the similar performance.